Fast 4D FEM Model for EIT Source Separation Benchmarking
The accurate separation of cardiac and ventilatory contributions to electrical impedance tomography signals is crucial for complete and non-invasive cardiorespiratory monitoring. However, no consensus on a suitable source separation algorithm was achieved despite several proposals due to lacking sys...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2023-09-01
|
| Series: | Current Directions in Biomedical Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/cdbme-2023-1097 |
| _version_ | 1797646291908427776 |
|---|---|
| author | Silva Diogo Filipe Leonhardt Steffen |
| author_facet | Silva Diogo Filipe Leonhardt Steffen |
| author_sort | Silva Diogo Filipe |
| collection | DOAJ |
| description | The accurate separation of cardiac and ventilatory contributions to electrical impedance tomography signals is crucial for complete and non-invasive cardiorespiratory monitoring. However, no consensus on a suitable source separation algorithm was achieved despite several proposals due to lacking systematic evaluation. To address this, we propose a benchmarking 4D finite element method generative model for mixed, cardiac, and ventilatory signals. Our model implements dynamic modelling of the heart, lungs, and pulmonary arteries using realistic volume and flow curve templates, along with cardiac and respiratory frequency coupling.We also employed variable alveolar and blood conductivities. The model was able to obtain long recordings faster than comparably complex models while maintaining significant physiological effects and signal properties such as non-stationarity, spatial delays, time and frequency profiles. The realistic physiological model can be used to taxonomize and evaluate source separation algorithms, as well as aid in the development and training of new ones. |
| first_indexed | 2024-03-11T15:00:31Z |
| format | Article |
| id | doaj.art-27353ef184ba4ebda57043ec5751a825 |
| institution | Directory Open Access Journal |
| issn | 2364-5504 |
| language | English |
| last_indexed | 2024-03-11T15:00:31Z |
| publishDate | 2023-09-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Current Directions in Biomedical Engineering |
| spelling | doaj.art-27353ef184ba4ebda57043ec5751a8252023-10-30T07:58:12ZengDe GruyterCurrent Directions in Biomedical Engineering2364-55042023-09-019138739010.1515/cdbme-2023-1097Fast 4D FEM Model for EIT Source Separation BenchmarkingSilva Diogo Filipe0Leonhardt Steffen1Chair for Medical Information Technology, RWTH Aachen, Pauwelsstr. 20, Aachen, GermanyChair for Medical Information Technology, RWTH Aachen, Pauwelsstr. 20, Aachen, GermanyThe accurate separation of cardiac and ventilatory contributions to electrical impedance tomography signals is crucial for complete and non-invasive cardiorespiratory monitoring. However, no consensus on a suitable source separation algorithm was achieved despite several proposals due to lacking systematic evaluation. To address this, we propose a benchmarking 4D finite element method generative model for mixed, cardiac, and ventilatory signals. Our model implements dynamic modelling of the heart, lungs, and pulmonary arteries using realistic volume and flow curve templates, along with cardiac and respiratory frequency coupling.We also employed variable alveolar and blood conductivities. The model was able to obtain long recordings faster than comparably complex models while maintaining significant physiological effects and signal properties such as non-stationarity, spatial delays, time and frequency profiles. The realistic physiological model can be used to taxonomize and evaluate source separation algorithms, as well as aid in the development and training of new ones.https://doi.org/10.1515/cdbme-2023-1097electrical impedance tomographyfinite element methodventilationperfusionbioimpedance |
| spellingShingle | Silva Diogo Filipe Leonhardt Steffen Fast 4D FEM Model for EIT Source Separation Benchmarking Current Directions in Biomedical Engineering electrical impedance tomography finite element method ventilation perfusion bioimpedance |
| title | Fast 4D FEM Model for EIT Source Separation Benchmarking |
| title_full | Fast 4D FEM Model for EIT Source Separation Benchmarking |
| title_fullStr | Fast 4D FEM Model for EIT Source Separation Benchmarking |
| title_full_unstemmed | Fast 4D FEM Model for EIT Source Separation Benchmarking |
| title_short | Fast 4D FEM Model for EIT Source Separation Benchmarking |
| title_sort | fast 4d fem model for eit source separation benchmarking |
| topic | electrical impedance tomography finite element method ventilation perfusion bioimpedance |
| url | https://doi.org/10.1515/cdbme-2023-1097 |
| work_keys_str_mv | AT silvadiogofilipe fast4dfemmodelforeitsourceseparationbenchmarking AT leonhardtsteffen fast4dfemmodelforeitsourceseparationbenchmarking |